---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-base-libri-demo-feature_extractor_not_frozen
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hubert-base-libri-demo-feature_extractor_not_frozen

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8505
- Wer: 1.0

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.00015
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 4.3787        | 1.12  | 500   | 3.5514          | 1.0 |
| 2.8772        | 2.24  | 1000  | 3.6079          | 1.0 |
| 2.8665        | 3.36  | 1500  | 4.0086          | 1.0 |
| 2.864         | 4.48  | 2000  | 4.0925          | 1.0 |
| 2.8606        | 5.61  | 2500  | 3.8393          | 1.0 |
| 2.8589        | 6.73  | 3000  | 3.7722          | 1.0 |
| 2.8603        | 7.85  | 3500  | 3.8588          | 1.0 |
| 2.8685        | 8.97  | 4000  | 3.8065          | 1.0 |
| 2.8602        | 10.09 | 4500  | 3.8807          | 1.0 |
| 2.858         | 11.21 | 5000  | 3.8724          | 1.0 |
| 2.8582        | 12.33 | 5500  | 3.8091          | 1.0 |
| 2.8579        | 13.45 | 6000  | 3.6785          | 1.0 |
| 2.8569        | 14.57 | 6500  | 3.7339          | 1.0 |
| 2.8574        | 15.7  | 7000  | 3.7972          | 1.0 |
| 2.8564        | 16.82 | 7500  | 3.8758          | 1.0 |
| 2.8569        | 17.94 | 8000  | 3.9114          | 1.0 |
| 2.8569        | 19.06 | 8500  | 3.9208          | 1.0 |
| 2.8565        | 20.18 | 9000  | 3.9229          | 1.0 |
| 2.8571        | 21.3  | 9500  | 3.8876          | 1.0 |
| 2.8569        | 22.42 | 10000 | 3.8732          | 1.0 |
| 2.8557        | 23.54 | 10500 | 3.8587          | 1.0 |
| 2.8569        | 24.66 | 11000 | 3.8505          | 1.0 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3